Database Self-Diagnosis Using NLP and Knowledge Evaluation

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Solution Overview

Problem

Current database management systems lack the capability for real-time automatic diagnosis and self-healing, leading to inefficiencies in error detection and repair, which increases troubleshooting time and costs.

Innovation Solution

A processor-based system that classifies problem descriptions using natural language processing and database-specific content evaluation to identify and solve issues autonomously, combining natural language processing techniques with database knowledge to provide immediate diagnostic solutions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If manual database troubleshooting is performed, then diagnostic accuracy can be maintained, but troubleshooting time and operational costs increase significantly

Engineering Contradiction:

Improvetroubleshooting timeVSAvoidautomatic diagnosis capability

Core Design Contradiction:

Loss of timeVSExtent of automation

Solution Approach 1:

The database system performs self-diagnosis by automatically analyzing problem descriptions, evaluating database objects and operations, and generating diagnostic results without requiring manual intervention from database administrators, thereby reducing troubleshooting time while maintaining diagnostic capability

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical troubleshooting processes with an automated electronic system that uses processors to execute diagnostic algorithms, evaluate database states, and generate solutions, substituting human-operated mechanical procedures with automated computational processes

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If comprehensive database evaluation is performed, then diagnostic accuracy improves, but system complexity and processing resources increase

Engineering Contradiction:

Improvediagnostic accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The diagnostic system segments the problem evaluation process into distinct modules: natural language processing for problem description analysis, database object evaluation, operation evaluation, and result generation. Each module handles a specific aspect of the diagnosis, improving accuracy while managing system complexity through modular design

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The evaluation system is designed to handle multiple types of database objects (tables, indexes, views) and operations (queries, updates, deletions) using a unified framework, allowing comprehensive diagnostic coverage without proportionally increasing system complexity

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11822528B2Database self-diagnosis and self-healing

Publication Date: 2023.11.21 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

In an approach for database self-diagnosis and self-healing, a processor receives a problem description related to a database. A processor classifies the problem description into a natural language description portion and a database-know-who content portion. A processor processes the natural language description portion using natural language processing techniques. A processor evaluates the database-know-who content portion. A processor combines a result of processing the natural language description portion and evaluating the database-know-who content portion. A processor identifies a solution based on the problem description and the combined result. A processor solves a problem using the identified solution.